This disclosure relates generally to digital photography. More particularly, but not by way of limitation, this disclosure relates to a technique for calibrating a pair of image capture devices using a face or other standard object as a calibration standard. As used herein, the term “camera” means any device that has at least two image capture units, each capable of capturing an image of a scene at substantially the same time (e.g., concurrently). This definition explicitly includes stand-alone digital cameras and image capture systems embedded in other devices such as mobile telephones, portable computer systems including tablet computer systems, and personal entertainment devices.
Two cameras may be used to generate stereoscopic images, depth maps and disparity maps. Two-camera systems may also be used to improve or assist image registration and fusion operations. To accomplish this however, the cameras need to be calibrated to one another. That is, the pose of the first camera with respect to the second camera needs to be known. Referring to FIG. 1, illustrative system 100 includes camera 105 having first and second image capture units 110 and 115. Image capture unit 110 has field of view (FOV) 120 and image capture unit 115 has FOV 125. When accurate machining and motion control is available, planar calibration target 130 or camera 105 may be moved in a controlled manner. During such motion, initial estimates for each capture unit's pose may be obtained and used in combination with calibration target 130's known structure/geometry and each image capture unit's known intrinsic parameters (e.g., focal lengths, skew, and optical center) to calibrate the two image capture devices. Key to this process is precise knowledge of the calibration object's structure or geometry. Once device 105 enters the consumer market, the availability of known calibration objects is lost. Further, the calibration of such units may change over time as they are subject to, for example, ballistic motions (e.g., being dropped) and thermal stresses. A loss of calibration can, in turn, reduce the quality of the three dimensional information available from such systems thereby negatively impacting operations relying on that information.